Other COVID datasets

Results

Setup

functions

Mean function for ggplot2 plots

meanFunction <- function(x){
  return(data.frame(y=round(mean(x),2),label=round(mean(x,na.rm=T),2)))}

themes to use with ggplot2

themes_ggplot <- theme_bw() +
  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank())+
  font("xlab", size = 12, color = "black", face = "bold") +
  font("ylab", size = 12, color = "black", face = "bold") +
  font("title", size = 14, color = "black", face = "bold")+
  font("legendtitle", size = 12, color = "black", face = "bold")+
  font("legendtext", size = 12, color = "black")+
  font("xy.text", size = 12, color = "black")+
  font("ylab", size = 12, color = "black", face = "bold") +
  font("xlab", size = 12, color = "black", face = "bold") +
  theme(strip.text.x = element_text( size = 12, color = "black", face = "bold"))+
  theme(strip.text.y = element_text( size = 12, color = "black", face = "bold"))+
  theme(legend.position='top')

chosen_colors = c("#9ecae1", "#a63603", "#e6550d", "#fd8d3c", "#fdbe85", "#feedde") 

general parameters

OUT_DIR <- "results/small_datasets/"
sra_table_path <- "raw/small_datasets/unitedCoronaSRATable.csv"
dir.create(OUT_DIR)

## Warning in dir.create(OUT_DIR): 'results/small_datasets' already exists

# dbgap_data_path <- "/private9/Projects/COVID_NASAL_DBGAP_TEMPORARY/temp_krt_dbgap/combined_sample_subject_attribute.csv"

# dbgap_table <- read.csv(file= dbgap_data_path, stringsAsFactors=FALSE)
sra_table <- read.csv(file= sra_table_path, stringsAsFactors=FALSE, sep=",")

sra_table$Group[sra_table$Project == "Nasal Swabs (GSE166530)" & sra_table$Group == "Controls"] <- "temp"
sra_table$Group[sra_table$Project == "Nasal Swabs (GSE166530)" & sra_table$Group == "COVID"] <- "Controls"
sra_table$Group[sra_table$Project == "Nasal Swabs (GSE166530)" & sra_table$Group == "temp"] <- "COVID"
sra_table$Group[sra_table$Project == "Nasal Swabs (GSE166530)" & sra_table$Group == "COVID"] <- "Controls"
sra_table$Group[sra_table$Group == "Controls"] <- "Control"

sra_table$Project <- factor(sra_table$Project,levels = c('Nasal Swabs (GSE166530)','Whole Blood (GSE167000)',
                                                     'Whole Blood (GSE171110)','Leukocytes (GSE157103)'))

kable(head(sra_table)) %>%
  kable_styling(bootstrap_options = c("striped", "hover", 'condensed')) 

Run	Project	Source	Group	Subject
SRR12544421	Leukocytes (GSE157103)	leukocyte	COVID-19	GSM4753022
SRR12544422	Leukocytes (GSE157103)	leukocyte	COVID-19	GSM4753022
SRR12544423	Leukocytes (GSE157103)	leukocyte	COVID-19	GSM4753023
SRR12544424	Leukocytes (GSE157103)	leukocyte	COVID-19	GSM4753023
SRR12544425	Leukocytes (GSE157103)	leukocyte	COVID-19	GSM4753024
SRR12544426	Leukocytes (GSE157103)	leukocyte	COVID-19	GSM4753024

Analysis tables

SALMON

ADARexp = c("raw/small_datasets/Covid19_GSE157103_SalmonTPM_ADAR.wideSamples.csv",
            "raw/small_datasets/WholeBlood_GSE171110_SalmonTPM_ADAR.wideSamples.csv",
            "raw/small_datasets/Blood_GSE167000_SalmonTPM_ADAR.wideSamples.csv",
            "raw/small_datasets/nasal_swabs_GSE166530_ADAR.wideSamples.csv")

#read all files to one table

df_salmon = ADARexp %>%
  map_dfr(compose(function (f) dcast(f, Sample~GeneSymbol),
                  function (f) melt(f, variable.name = "Sample", id.var = "GeneSymbol", value.name = "TPM"),
                  function (f) fread(f, header=T, check.names = F, stringsAsFactors=FALSE))) %>%
  filter(!grepl(pattern = "_counts", x = Sample)) %>%
  mutate(Sample = gsub("_TPM", replacement = "", x = Sample)) 

## Using 'TPM' as value column. Use 'value.var' to override
## Using 'TPM' as value column. Use 'value.var' to override
## Using 'TPM' as value column. Use 'value.var' to override
## Using 'TPM' as value column. Use 'value.var' to override

kable(head(df_salmon)) %>%
  kable_styling(bootstrap_options = c("striped", "hover", 'condensed')) 

Sample	ADAR	ADARB1	ADARB2	ADARB2-AS1
SRR12544419	368.004	6.04658	0.061325	0
SRR12544420	366.173	8.26516	0.000000	0
SRR12544421	163.731	4.80513	0.000000	0
SRR12544422	175.065	3.94874	0.000000	0
SRR12544423	349.408	3.03863	0.000000	0
SRR12544424	348.612	2.32348	0.000000	0

ISG

ISG_path <- c("raw/small_datasets/Covid19_GSE157103_ArticleCalcLog2_ISG_madz_scores.csv",
        "raw/small_datasets/WholeBlood_GSE171110_ArticleCalcLog2_ISG_madz_scores.csv",
        "raw/small_datasets/Blood_GSE167000_ArticleCalcLog2_ISG_madz_scores.csv",
        "raw/small_datasets/Covid_nasal_swabs_GSE166530_ArticleCalcLog2_ISG_madz_scores.csv")

df_isg = ISG_path %>% 
  map_dfr(fread, header = T, stringsAsFactors = F)  %>%
filter(!grepl(pattern = "_counts", x = Sample)) %>%
  mutate(Sample = gsub("_TPM", replacement = "", x = Sample)) 

kable(head(df_isg)) %>%
  kable_styling(bootstrap_options = c("striped", "hover", 'condensed')) 

Sample	ISG38_score
SRR12544419	1.4220689
SRR12544420	1.4264640
SRR12544421	0.0092516
SRR12544422	0.0248549
SRR12544423	1.4387706
SRR12544424	1.4381190

STAR

STAR = c("raw/small_datasets/Covid19_GSE157103_STAR_stats.csv",
        "raw/small_datasets/WholeBlood_GSE171110_STAR_stats.csv",
        "raw/small_datasets/Blood_GSE167000_STAR_stats.csv",
        "raw/small_datasets/Covid_nasal_swabs_GSE166530_STAR_stats.csv")

STAR_stats = STAR %>% 
  map_dfr(fread, header = T, stringsAsFactors = F) 

kable(head(STAR_stats)) %>%
  kable_styling(bootstrap_options = c("striped", "hover", 'condensed')) 

Sample	Number of input reads	Average input read length	Uniquely mapped reads number	Uniquely mapped reads %	Average mapped length	Number of splices: Total	Number of splices: Annotated (sjdb)	Number of splices: GT/AG	Number of splices: GC/AG	Number of splices: AT/AC	Number of splices: Non-canonical	Mismatch rate per base %	Deletion rate per base	Deletion average length	Insertion rate per base	Insertion average length	Number of reads mapped to multiple loci	% of reads mapped to multiple loci	Number of reads mapped to too many loci	% of reads mapped to too many loci	Number of reads unmapped: too many mismatches	% of reads unmapped: too many mismatches	Number of reads unmapped: too short	% of reads unmapped: too short	Number of reads unmapped: other	% of reads unmapped: other	Number of chimeric reads	% of chimeric reads
SRR12544455	15006318	102	12417854	82.75	101.68	3612887	3566408	3578305	26150	2983	5449	0.22	0.00	1.49	0	1.33	0	0	1183602	7.89	0	0	1397839	9.32	7023	0.05	0	0
SRR12544419	15588448	102	12936578	82.99	101.69	4236774	4188200	4198293	29657	3759	5065	0.21	0.00	1.46	0	1.30	0	0	1189641	7.63	0	0	1454754	9.33	7475	0.05	0	0
SRR12544454	13608114	102	11737417	86.25	101.69	3658305	3606749	3624765	25202	3018	5320	0.22	0.00	1.47	0	1.31	0	0	1257326	9.24	0	0	607018	4.46	6353	0.05	0	0
SRR12544420	15431677	102	12800775	82.95	101.69	4193008	4144994	4154429	29742	3804	5033	0.23	0.00	1.46	0	1.29	0	0	1181697	7.66	0	0	1441952	9.34	7253	0.05	0	0
SRR12544421	9258530	102	7836692	84.64	101.70	2474920	2443621	2452500	17277	1997	3146	0.22	0.00	1.39	0	1.31	0	0	888586	9.60	0	0	528857	5.71	4395	0.05	0	0
SRR12544463	12823761	102	10446156	81.46	101.68	2716139	2679307	2691212	18952	2153	3822	0.22	0.01	1.41	0	1.35	0	0	952437	7.43	0	0	1419432	11.07	5736	0.04	0	0

Alu-index

aluIndex_path = c("raw/small_datasets/Covid19_GSE157103_EditingIndex.csv",
             "raw/small_datasets/WholeBlood_GSE171110_EditingIndex.csv",
             "raw/small_datasets/Blood_GSE167000_EditingIndex.csv",
             "raw/small_datasets/Covid_nasal_swabs_GSE166530_EditingIndex.csv")

#read all files to one table
aluIndex = aluIndex_path %>% 
  map_dfr(fread, header = T, stringsAsFactors = F) %>% 
  dplyr::select("Sample","A2GEditingIndex","A2TEditingIndex","C2AEditingIndex",
                "C2TEditingIndex", "C2GEditingIndex","A2CEditingIndex")

#change the column names
names(aluIndex) <- gsub("EditingIndex","EditingIndex_Alu",
                        names(aluIndex))

kable(head(aluIndex)) %>%
  kable_styling(bootstrap_options = c("striped", "hover", 'condensed')) 

Sample	A2GEditingIndex_Alu	A2TEditingIndex_Alu	C2AEditingIndex_Alu	C2TEditingIndex_Alu	C2GEditingIndex_Alu	A2CEditingIndex_Alu
SRR12544643	1.2274776	0.0599239	0.0617665	0.1894718	0.0461365	0.0534655
SRR12544640	1.0706102	0.0519371	0.0487548	0.1440984	0.0377717	0.0427339
SRR12544479	1.0688495	0.0437524	0.0458131	0.1324161	0.0296800	0.0346312
SRR12544517	0.8622589	0.0493260	0.0511186	0.1189223	0.0334008	0.0434031
SRR12544489	1.1620090	0.0501233	0.0551385	0.1709712	0.0399206	0.0451556
SRR12544522	1.0952535	0.0538721	0.0614048	0.1614525	0.0457137	0.0462310

combine the plots

#combine all tables to one table
df_combined <- left_join(sra_table, df_salmon ,by=c("Run"="Sample")) %>%
  left_join(df_isg ,by=c("Run"="Sample")) %>%
  left_join(aluIndex,by=c("Run"="Sample")) %>%
  left_join(STAR_stats,by=c("Run"="Sample"))

out_path <- paste0(OUT_DIR,"/combinedResults_all.csv")
write.csv(df_combined, out_path, row.names = F, quote = F)

kable(head(df_combined)) %>%
  kable_styling(bootstrap_options = c("striped", "hover", 'condensed')) 

Run	Project	Source	Group	Subject	ADAR	ADARB1	ADARB2	ADARB2-AS1	ISG38_score	A2GEditingIndex_Alu	A2TEditingIndex_Alu	C2AEditingIndex_Alu	C2TEditingIndex_Alu	C2GEditingIndex_Alu	A2CEditingIndex_Alu	Number of input reads	Average input read length	Uniquely mapped reads number	Uniquely mapped reads %	Average mapped length	Number of splices: Total	Number of splices: Annotated (sjdb)	Number of splices: GT/AG	Number of splices: GC/AG	Number of splices: AT/AC	Number of splices: Non-canonical	Mismatch rate per base %	Deletion rate per base	Deletion average length	Insertion rate per base	Insertion average length	Number of reads mapped to multiple loci	% of reads mapped to multiple loci	Number of reads mapped to too many loci	% of reads mapped to too many loci	Number of reads unmapped: too many mismatches	% of reads unmapped: too many mismatches	Number of reads unmapped: too short	% of reads unmapped: too short	Number of reads unmapped: other	% of reads unmapped: other	Number of chimeric reads	% of chimeric reads
SRR12544421	Leukocytes (GSE157103)	leukocyte	COVID-19	GSM4753022	163.731	4.80513	0.000000	0	0.0092516	1.052801	0.0452625	0.0427253	0.1282110	0.0326654	0.0381811	9258530	102	7836692	84.64	101.70	2474920	2443621	2452500	17277	1997	3146	0.22	0.00	1.39	0	1.31	0	0	888586	9.60	0	0	528857	5.71	4395	0.05	0	0
SRR12544422	Leukocytes (GSE157103)	leukocyte	COVID-19	GSM4753022	175.065	3.94874	0.000000	0	0.0248549	1.043986	0.0469718	0.0479044	0.1329852	0.0347423	0.0379615	9151662	102	7743902	84.62	101.69	2450458	2419100	2428365	16879	2062	3152	0.24	0.00	1.39	0	1.32	0	0	880380	9.62	0	0	523164	5.72	4216	0.05	0	0
SRR12544423	Leukocytes (GSE157103)	leukocyte	COVID-19	GSM4753023	349.408	3.03863	0.000000	0	1.4387706	1.298069	0.0442355	0.0479175	0.1484962	0.0396385	0.0395406	13238599	102	11325557	85.55	101.70	3180001	3127132	3150636	22548	2697	4120	0.21	0.00	1.49	0	1.33	0	0	1186839	8.96	0	0	720607	5.44	5596	0.04	0	0
SRR12544424	Leukocytes (GSE157103)	leukocyte	COVID-19	GSM4753023	348.612	2.32348	0.000000	0	1.4381190	1.286904	0.0496128	0.0516164	0.1481855	0.0408331	0.0443446	13102365	102	11198594	85.47	101.69	3146771	3094910	3118163	21950	2655	4003	0.23	0.00	1.49	0	1.34	0	0	1181938	9.02	0	0	716379	5.47	5454	0.04	0	0
SRR12544425	Leukocytes (GSE157103)	leukocyte	COVID-19	GSM4753024	134.683	7.86667	0.000000	0	-0.0118132	1.008229	0.0561895	0.0522114	0.1764840	0.0432753	0.0471505	13924194	102	10880240	78.14	101.66	3391078	3349157	3360426	23663	2853	4136	0.23	0.00	1.51	0	1.31	0	0	1083481	7.78	0	0	1954801	14.04	5672	0.04	0	0
SRR12544426	Leukocytes (GSE157103)	leukocyte	COVID-19	GSM4753024	138.416	9.47355	0.022476	0	-0.0054734	1.000815	0.0621749	0.0578964	0.1775207	0.0461696	0.0484435	13774083	102	10760249	78.12	101.65	3352312	3311124	3321848	23545	2843	4076	0.25	0.01	1.51	0	1.31	0	0	1074460	7.80	0	0	1933765	14.04	5609	0.04	0	0

General statistics

df_combined_Stats <- df_combined %>% 
  group_by(Project,Group) %>% #nrow()
  summarize(ADAR = paste(round(mean(ADAR, na.rm=T),2), "(",round(min(ADAR,na.rm=T),2),", ", 
                         round(max(ADAR,na.rm=T),2),", ",round(median(ADAR,na.rm=T),2),", +-",
                         round(sd(ADAR,na.rm=T),2),")"),
            ADARB1 = paste(round(mean(ADARB1,na.rm=T),2), "(",round(min(ADARB1,na.rm=T),2),", ", 
                           round(max(ADARB1,na.rm=T),2),", ",round(median(ADARB1,na.rm=T),2),", +-",
                           round(sd(ADARB1,na.rm=T),2),")"),
            ADARB2 = paste(round(mean(ADARB2,na.rm=T),2), "(",round(min(ADARB2,na.rm=T),2),", ", 
                           round(max(ADARB2,na.rm=T),2),", ",round(median(ADARB2,na.rm=T),2),", +-",
                           round(sd(ADARB2,na.rm=T),2),")"),
            ADARB2.AS1 = paste(round(mean(`ADARB2-AS1`,na.rm=T),2), "(",round(min(`ADARB2-AS1`,na.rm=T),2),", ", 
                               round(max(`ADARB2-AS1`,na.rm=T),2),", ",round(median(`ADARB2-AS1`,na.rm=T),2),", +-",
                               round(sd(`ADARB2-AS1`,na.rm=T),2),")"),
            ISG38_score = paste(round(mean(ISG38_score,na.rm=T),2), "(",round(min(ISG38_score,na.rm=T),2),", ", 
                                round(max(ISG38_score,na.rm=T),2),", ",round(median(ISG38_score,na.rm=T),2), ", +-",
                                round(sd(ISG38_score,na.rm=T),2),")"),
           A2GEditingIndex_Alu = paste(round(mean(A2GEditingIndex_Alu,na.rm=T),2), "(",
                                       round(min(A2GEditingIndex_Alu,na.rm=T),2),", ", 
                                    round(max(A2GEditingIndex_Alu, na.rm=T),2),", ",
                                    round(median(A2GEditingIndex_Alu, na.rm=T),2), ", +-", 
                                    round(sd(A2GEditingIndex_Alu, na.rm=T),2),")")
            ) 

## `summarise()` has grouped output by 'Project'. You can override using the
## `.groups` argument.

write.csv(df_combined_Stats, paste0(OUT_DIR,"/combinedResults_mean_min_max_median_sd.csv"), 
          row.names = F, quote = F)

kable(df_combined_Stats) %>%
  kable_styling(bootstrap_options = c("striped", "hover", 'condensed')) 

Project	Group	ADAR	ADARB1	ADARB2	ADARB2.AS1	ISG38_score	A2GEditingIndex_Alu
Nasal Swabs (GSE166530)	Control	9.14 ( 7.21 , 14.39 , 7.75 , +- 3 )	1.09 ( 0.46 , 2.22 , 0.66 , +- 0.77 )	1.23 ( 0.25 , 2.81 , 1.05 , +- 0.98 )	0.6 ( 0 , 2.6 , 0 , +- 1.13 )	0.13 ( -0.05 , 0.67 , -0.03 , +- 0.31 )	0.63 ( 0.29 , 0.89 , 0.64 , +- 0.27 )
Nasal Swabs (GSE166530)	COVID-19	14.85 ( 0.27 , 117.56 , 6.96 , +- 23.2 )	0.86 ( 0 , 6.77 , 0.39 , +- 1.37 )	0.31 ( 0 , 0.9 , 0.26 , +- 0.23 )	0.01 ( 0 , 0.2 , 0 , +- 0.03 )	0.08 ( -1.15 , 1.85 , -0.01 , +- 0.74 )	2.74 ( 0.53 , 5.3 , 2.52 , +- 1.06 )
Whole Blood (GSE167000)	Control	94.2 ( 41.24 , 156.32 , 84.43 , +- 33.77 )	5.91 ( 1.43 , 14.31 , 4.46 , +- 3.79 )	0.83 ( 0 , 7.6 , 0 , +- 1.97 )	0 ( 0 , 0 , 0 , +- 0 )	-0.6 ( -0.88 , -0.26 , -0.62 , +- 0.13 )	1.33 ( 1.12 , 1.46 , 1.35 , +- 0.09 )
Whole Blood (GSE167000)	COVID-19	139.54 ( 54.87 , 286.61 , 130.65 , +- 63.14 )	5.51 ( 2.14 , 9.46 , 4.7 , +- 2.12 )	0.79 ( 0 , 6.76 , 0 , +- 1.88 )	0 ( 0 , 0 , 0 , +- 0 )	-0.39 ( -0.78 , 0.01 , -0.42 , +- 0.23 )	1.43 ( 1.19 , 1.69 , 1.45 , +- 0.13 )
Whole Blood (GSE171110)	Control	174.56 ( 123.25 , 285.98 , 167.92 , +- 35.36 )	15.36 ( 6.16 , 47.17 , 12.83 , +- 8.99 )	0.47 ( 0 , 3.76 , 0 , +- 0.8 )	0 ( 0 , 0 , 0 , +- 0 )	-0.27 ( -0.49 , 0.51 , -0.38 , +- 0.28 )	1.44 ( 1.34 , 1.67 , 1.43 , +- 0.09 )
Whole Blood (GSE171110)	COVID-19	256.1 ( 126.24 , 532.3 , 235.07 , +- 75.27 )	12.8 ( 1.13 , 127.56 , 10.2 , +- 11.75 )	2.65 ( 0 , 18.83 , 0.05 , +- 4.38 )	0.01 ( 0 , 1.46 , 0 , +- 0.12 )	0.17 ( -0.73 , 1.62 , 0.06 , +- 0.6 )	1.72 ( 1.37 , 2.07 , 1.72 , +- 0.18 )
Leukocytes (GSE157103)	Control	96.59 ( 24.16 , 176.28 , 90.93 , +- 45.08 )	3.59 ( 0.49 , 8.54 , 3.33 , +- 1.99 )	0.91 ( 0 , 3.9 , 0.53 , +- 1.09 )	0 ( 0 , 0.2 , 0 , +- 0.03 )	-0.35 ( -1.56 , 0.63 , -0.45 , +- 0.46 )	1 ( 0.81 , 1.18 , 1 , +- 0.07 )
Leukocytes (GSE157103)	COVID-19	165.08 ( 17.7 , 382.3 , 163.74 , +- 79.22 )	4 ( 0.15 , 14.41 , 3.66 , +- 2.47 )	1.23 ( 0 , 12.77 , 0.07 , +- 2.11 )	0.01 ( 0 , 0.89 , 0 , +- 0.07 )	0.1 ( -1.51 , 1.44 , -0.01 , +- 0.6 )	1.1 ( 0.86 , 1.39 , 1.1 , +- 0.1 )

Plots

Alu-Index

A-G clean signal

#Leukocytes (GSE157103)  Nasal Swabs (GSE166530) Whole Blood (GSE167000) Whole Blood (GSE171110)

 edit_type_names <- c("A2GEditingIndex_Alu" = "A-G\n(T-C)", "A2TEditingIndex_Alu" = "A-T\n(T-A)", 
                      "C2AEditingIndex_Alu" = "C-A\n(G-T)", "C2TEditingIndex_Alu" = "C-T\n(G-A)", 
                      "C2GEditingIndex_Alu" = "C-G\n(G-C)",  "A2CEditingIndex_Alu" = "A-C\n(T-G)")

plot_GSE157103.Mismatches <-
  df_combined %>%
  filter(Project =="Leukocytes (GSE157103)") %>%
  dplyr::select("Run", "Project", 
                "A2GEditingIndex_Alu","A2TEditingIndex_Alu",
         "C2AEditingIndex_Alu","C2TEditingIndex_Alu",
         "C2GEditingIndex_Alu","A2CEditingIndex_Alu") %>%
  gather(edit_type, value, -Run, -Project) %>%
  ggplot(aes(y=value, x=edit_type ,fill=edit_type))+
  geom_boxplot(aes(fill=edit_type)) +  
  themes_ggplot+
  facet_grid(~Project)+
  # theme(axis.text.x = element_text(angle = 90))+
  ylab("ALU Editing Index")+ xlab ("Nucleotide mismatch")+
  scale_fill_discrete(name = "Mistmatch:")+
  theme(axis.title.x = element_blank())+ theme(legend.position = "none") +
  scale_fill_manual(values=c("yellow", "red", "blue", "green", "orange", "black"))+
  scale_x_discrete(labels= edit_type_names)

## Scale for 'fill' is already present. Adding another scale for 'fill', which
## will replace the existing scale.

plot_GSE157103.Mismatches

#Leukocytes (GSE157103)  Nasal Swabs (GSE166530) Whole Blood (GSE167000) Whole Blood (GSE171110)

plot_GSE166530.Mismatches <-
  df_combined %>%
  filter(Project =="Nasal Swabs (GSE166530)") %>%
  dplyr::select("Run", "Project", 
                "A2GEditingIndex_Alu","A2TEditingIndex_Alu",
         "C2AEditingIndex_Alu","C2TEditingIndex_Alu",
         "C2GEditingIndex_Alu","A2CEditingIndex_Alu") %>%
  gather(edit_type, value, -Run, -Project) %>%
  ggplot(aes(y=value, x=edit_type ,fill=edit_type))+
  geom_boxplot(aes(fill=edit_type)) +  
  themes_ggplot+
  facet_grid(~Project)+
  # theme(axis.text.x = element_text(angle = 90))+
  ylab("ALU Editing Index")+ xlab ("Nucleotide mismatch")+
  scale_fill_discrete(name = "Mistmatch:")+
  theme(axis.title.x = element_blank())+ theme(legend.position = "none") +
  scale_fill_manual(values=c("yellow", "red", "blue", "green", "orange", "black"))+
  scale_x_discrete(labels= edit_type_names)

## Scale for 'fill' is already present. Adding another scale for 'fill', which
## will replace the existing scale.

plot_GSE166530.Mismatches

#Leukocytes (GSE157103)  Nasal Swabs (GSE166530) Whole Blood (GSE167000) Whole Blood (GSE171110)

plot_GSE167000.Mismatches <-
  df_combined %>%
  filter(Project =="Whole Blood (GSE167000)") %>%
  dplyr::select("Run", "Project", 
                "A2GEditingIndex_Alu","A2TEditingIndex_Alu",
         "C2AEditingIndex_Alu","C2TEditingIndex_Alu",
         "C2GEditingIndex_Alu","A2CEditingIndex_Alu") %>%
  gather(edit_type, value, -Run, -Project) %>%
  ggplot(aes(y=value, x=edit_type ,fill=edit_type))+
  geom_boxplot(aes(fill=edit_type)) +  
  themes_ggplot+
  facet_grid(~Project)+
  # theme(axis.text.x = element_text(angle = 90))+
  ylab("ALU Editing Index")+ xlab ("Nucleotide mismatch")+
  scale_fill_discrete(name = "Mistmatch:")+
  theme(axis.title.x = element_blank())+ theme(legend.position = "none") +
  scale_fill_manual(values=c("yellow", "red", "blue", "green", "orange", "black"))+
  scale_x_discrete(labels= edit_type_names)

## Scale for 'fill' is already present. Adding another scale for 'fill', which
## will replace the existing scale.

plot_GSE167000.Mismatches

#Leukocytes (GSE157103)  Nasal Swabs (GSE166530) Whole Blood (GSE167000) Whole Blood (GSE171110)

plot_GSE171110.Mismatches <-
  df_combined %>%
  filter(Project =="Whole Blood (GSE171110)") %>%
  dplyr::select("Run", "Project", 
                "A2GEditingIndex_Alu","A2TEditingIndex_Alu",
         "C2AEditingIndex_Alu","C2TEditingIndex_Alu",
         "C2GEditingIndex_Alu","A2CEditingIndex_Alu") %>%
  gather(edit_type, value, -Run, -Project) %>%
  ggplot(aes(y=value, x=edit_type ,fill=edit_type))+
  geom_boxplot(aes(fill=edit_type)) +  
  themes_ggplot+
  facet_grid(~Project)+
  # theme(axis.text.x = element_text(angle = 90))+
  ylab("ALU Editing Index")+ xlab ("Nucleotide mismatch")+
  scale_fill_discrete(name = "Mistmatch:")+
  theme(axis.title.x = element_blank())+ theme(legend.position = "none") +
  scale_fill_manual(values=c("yellow", "red", "blue", "green", "orange", "black"))+
  scale_x_discrete(labels= edit_type_names)

## Scale for 'fill' is already present. Adding another scale for 'fill', which
## will replace the existing scale.

plot_GSE171110.Mismatches

#Leukocytes (GSE157103)  Nasal Swabs (GSE166530) Whole Blood (GSE167000) Whole Blood (GSE171110)

 plot_grid(plot_GSE166530.Mismatches, 
          plot_GSE167000.Mismatches,
          plot_GSE171110.Mismatches,
          plot_GSE157103.Mismatches,
          labels = c('', '','',''), label_size = 12, ncol=4)

out_path <- paste0(OUT_DIR,'/',"AluIndex_all_cleanSignal.pdf")
ggsave(out_path, width = 18, height = 6)         

Alu-Index

#Leukocytes (GSE157103)  Nasal Swabs (GSE166530) Whole Blood (GSE167000) Whole Blood (GSE171110)
y_position = max(df_combined%>% 
  filter(Project =="Leukocytes (GSE157103)") %>% .$A2GEditingIndex_Alu)

c <- df_combined %>% 
  filter(Project =="Leukocytes (GSE157103)") %>%
  compare_means(A2GEditingIndex_Alu ~Group, data = .)
c %<>% mutate(y_pos = c(y_position *1), 
              labels = ifelse(p < 0.05, sprintf("%2.1e",p),p))
# c <- c[c(1,3,2),] #reorder manually sorry
c$p.adj.format <- c$p.adj
c$p.adj.format[c$p.adj < 2e-16] <- "< 2e-16"
c$p.adj.format[as.numeric(c$p.adj) > 0.1] <- "N.S"

c$p.adj.format.stars <- c$p.adj
c$p.adj.format.stars[c$p.adj >= 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.05] <- paste0("* (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.01] <- paste0("** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.001] <- paste0("*** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 2e-16] <- paste0("**** (p=", c$p.adj,")")

df_c <- as.data.frame(c)

plot_GSE157103 <-
  df_combined %>%
  filter(Project =="Leukocytes (GSE157103)") %>%
  ggplot(
               aes(y=A2GEditingIndex_Alu, x=Group))+
  geom_boxplot(aes(fill=Group)) +  geom_jitter( size=2, alpha = 0.2)+
  facet_grid(  ~ Project ,  drop = TRUE, scales = "free", space = "free",)+
  themes_ggplot+ ylab("ALU Editing Index")+ xlab ("Group")+ scale_fill_discrete(name = "Group:")+
  expand_limits(y = 0) + scale_fill_manual(values=c("blue","red"))+
  theme(axis.title.x = element_blank())+ theme(legend.position = "none")+
  geom_signif(data = df_c, 
              aes(xmin=group1, xmax=group2, annotations=p.adj.format.stars, y_position=y_pos),manual = TRUE)

## Scale for 'fill' is already present. Adding another scale for 'fill', which
## will replace the existing scale.

## Warning: Ignoring unknown aesthetics: xmin, xmax, annotations, y_position

plot_GSE157103

#Leukocytes (GSE157103)  Nasal Swabs (GSE166530) Whole Blood (GSE167000) Whole Blood (GSE171110)
y_position = max(df_combined%>% 
  filter(Project =="Nasal Swabs (GSE166530)") %>% .$A2GEditingIndex_Alu)

c <- df_combined %>% 
  filter(Project =="Nasal Swabs (GSE166530)") %>%
  compare_means(A2GEditingIndex_Alu ~Group, data = .)
c %<>% mutate(y_pos = c(y_position *1), 
              labels = ifelse(p < 0.05, sprintf("%2.1e",p),p))
# c <- c[c(1,3,2),] #reorder manually sorry
c$p.adj.format <- c$p.adj
c$p.adj.format[c$p.adj < 2e-16] <- "< 2e-16"
c$p.adj.format[as.numeric(c$p.adj) > 0.1] <- "N.S"

c$p.adj.format.stars <- c$p.adj
c$p.adj.format.stars[c$p.adj >= 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.05] <- paste0("* (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.01] <- paste0("** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.001] <- paste0("*** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 2e-16] <- paste0("**** (p=", c$p.adj,")")

df_c <- as.data.frame(c)

plot_GSE166530 <-
  df_combined %>%
  filter(Project =="Nasal Swabs (GSE166530)") %>%
  ggplot(
               aes(y=A2GEditingIndex_Alu, x=Group))+
  geom_boxplot(aes(fill=Group)) +  geom_jitter( size=2, alpha = 0.2)+
  facet_grid(  ~ Project ,  drop = TRUE, scales = "free", space = "free",)+
  themes_ggplot+ ylab("ALU Editing Index")+ xlab ("Group")+ scale_fill_discrete(name = "Group:")+
  expand_limits(y = 0) + scale_fill_manual(values=c("blue","red"))+
  theme(axis.title.x = element_blank())+ theme(legend.position = "none")+
  geom_signif(data = df_c, 
              aes(xmin=group1, xmax=group2, annotations=p.adj.format.stars, y_position=y_pos),manual = TRUE)

## Scale for 'fill' is already present. Adding another scale for 'fill', which
## will replace the existing scale.

## Warning: Ignoring unknown aesthetics: xmin, xmax, annotations, y_position

plot_GSE166530

#Leukocytes (GSE157103)  Nasal Swabs (GSE166530) Whole Blood (GSE167000) Whole Blood (GSE171110)
y_position = max(df_combined%>% 
  filter(Project =="Whole Blood (GSE167000)") %>% .$A2GEditingIndex_Alu)

c <- df_combined %>% 
  filter(Project =="Whole Blood (GSE167000)") %>%
  compare_means(A2GEditingIndex_Alu ~Group, data = .)
c %<>% mutate(y_pos = c(y_position *1), 
              labels = ifelse(p < 0.05, sprintf("%2.1e",p),p))
# c <- c[c(1,3,2),] #reorder manually sorry
c$p.adj.format <- c$p.adj
c$p.adj.format[c$p.adj < 2e-16] <- "< 2e-16"
c$p.adj.format[as.numeric(c$p.adj) > 0.1] <- "N.S"

c$p.adj.format.stars <- c$p.adj
c$p.adj.format.stars[c$p.adj >= 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.05] <- paste0("* (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.01] <- paste0("** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.001] <- paste0("*** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 2e-16] <- paste0("**** (p=", c$p.adj,")")

df_c <- as.data.frame(c)

plot_GSE167000 <-
  df_combined %>%
  filter(Project =="Whole Blood (GSE167000)") %>%
  ggplot(
               aes(y=A2GEditingIndex_Alu, x=Group))+
  geom_boxplot(aes(fill=Group)) +  geom_jitter( size=2, alpha = 0.2)+
  facet_grid(  ~ Project ,  drop = TRUE, scales = "free", space = "free",)+
  themes_ggplot+ ylab("ALU Editing Index")+ xlab ("Group")+ scale_fill_discrete(name = "Group:")+
  expand_limits(y = 0) + scale_fill_manual(values=c("blue","red"))+
  theme(axis.title.x = element_blank())+ theme(legend.position = "none")+
  geom_signif(data = df_c, 
              aes(xmin=group1, xmax=group2, annotations=p.adj.format.stars, y_position=y_pos),manual = TRUE)

## Scale for 'fill' is already present. Adding another scale for 'fill', which
## will replace the existing scale.

## Warning: Ignoring unknown aesthetics: xmin, xmax, annotations, y_position

plot_GSE167000

#Leukocytes (GSE157103)  Nasal Swabs (GSE166530) Whole Blood (GSE167000) Whole Blood (GSE171110)
y_position = max(df_combined%>% 
  filter(Project =="Whole Blood (GSE171110)") %>% .$A2GEditingIndex_Alu)

c <- df_combined %>% 
  filter(Project =="Whole Blood (GSE171110)") %>%
  compare_means(A2GEditingIndex_Alu ~Group, data = .)
c %<>% mutate(y_pos = c(y_position *1), 
              labels = ifelse(p < 0.05, sprintf("%2.1e",p),p))
# c <- c[c(1,3,2),] #reorder manually sorry
c$p.adj.format <- c$p.adj
c$p.adj.format[c$p.adj < 2e-16] <- "< 2e-16"
c$p.adj.format[as.numeric(c$p.adj) > 0.1] <- "N.S"

c$p.adj.format.stars <- c$p.adj
c$p.adj.format.stars[c$p.adj >= 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.05] <- paste0("* (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.01] <- paste0("** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.001] <- paste0("*** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 2e-16] <- paste0("**** (p=", c$p.adj,")")

df_c <- as.data.frame(c)

plot_GSE171110 <-
  df_combined %>%
  filter(Project =="Whole Blood (GSE171110)") %>%
  ggplot(
               aes(y=A2GEditingIndex_Alu, x=Group))+
  geom_boxplot(aes(fill=Group)) +  geom_jitter( size=2, alpha = 0.2)+
  facet_grid(  ~ Project ,  drop = TRUE, scales = "free", space = "free",)+
  themes_ggplot+ ylab("ALU Editing Index")+ xlab ("Group")+ scale_fill_discrete(name = "Group:")+
  expand_limits(y = 0) + scale_fill_manual(values=c("blue","red"))+
  theme(axis.title.x = element_blank())+ theme(legend.position = "none")+
  geom_signif(data = df_c, 
              aes(xmin=group1, xmax=group2, annotations=p.adj.format.stars, y_position=y_pos),manual = TRUE)

## Scale for 'fill' is already present. Adding another scale for 'fill', which
## will replace the existing scale.

## Warning: Ignoring unknown aesthetics: xmin, xmax, annotations, y_position

plot_GSE171110

plot_grid(plot_GSE166530, plot_GSE167000, plot_GSE171110, plot_GSE157103,
          labels = c('', '','',''), label_size = 12, ncol=4)

out_path <- paste0(OUT_DIR,'/',"AluEditing_all_combined.pdf")
ggsave(out_path, width = 14, height = 6)

SALMON

Leukocytes (GSE157103)

#Leukocytes (GSE157103)  Nasal Swabs (GSE166530) Whole Blood (GSE167000) Whole Blood (GSE171110)
y_position = max(df_combined%>% 
  filter(Project =="Leukocytes (GSE157103)") %>% .$ADAR)

c <- df_combined %>% 
  filter(Project =="Leukocytes (GSE157103)") %>%
  compare_means(ADAR ~Group, data = .)
c %<>% mutate(y_pos = c(y_position *1), 
              labels = ifelse(p < 0.05, sprintf("%2.1e",p),p))
# c <- c[c(1,3,2),] #reorder manually sorry
c$p.adj.format <- c$p.adj
c$p.adj.format[c$p.adj < 2e-16] <- "< 2e-16"
c$p.adj.format[as.numeric(c$p.adj) > 0.1] <- "N.S"

c$p.adj.format.stars <- c$p.adj
c$p.adj.format.stars[c$p.adj >= 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.05] <- paste0("* (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.01] <- paste0("** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.001] <- paste0("*** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 2e-16] <- paste0("**** (p=", c$p.adj,")")

df_c <- as.data.frame(c)

plot_GSE157103.ADAR <-
  df_combined %>%
  filter(Project =="Leukocytes (GSE157103)") %>%
  ggplot(
               aes(y=ADAR, x=Group))+
  geom_boxplot(aes(fill=Group)) +  geom_jitter( size=2, alpha = 0.2)+
  # facet_grid( ~ Project ,  drop = TRUE, scales = "free", space = "free",)+
  themes_ggplot+ ylab("Normalized Expression (TPM)")+ xlab ("Group")+ scale_fill_discrete(name = "Group:")+
  expand_limits(y = 0) + scale_fill_manual(values=c("blue","red"))+
  theme(axis.title.x = element_blank())+ theme(legend.position = "none")+
  geom_signif(data = df_c, 
              aes(xmin=group1, xmax=group2, annotations=p.adj.format.stars, y_position=y_pos),manual = TRUE)

## Scale for 'fill' is already present. Adding another scale for 'fill', which
## will replace the existing scale.

## Warning: Ignoring unknown aesthetics: xmin, xmax, annotations, y_position

plot_GSE157103.ADAR

#Leukocytes (GSE157103)  Nasal Swabs (GSE166530) Whole Blood (GSE167000) Whole Blood (GSE171110)
y_position = max(df_combined%>% 
  filter(Project =="Leukocytes (GSE157103)") %>% .$ADARB1)

c <- df_combined %>% 
  filter(Project =="Leukocytes (GSE157103)") %>%
  compare_means(ADARB1 ~Group, data = .)
c %<>% mutate(y_pos = c(y_position *1), 
              labels = ifelse(p < 0.05, sprintf("%2.1e",p),p))
# c <- c[c(1,3,2),] #reorder manually sorry
c$p.adj.format <- c$p.adj
c$p.adj.format[c$p.adj < 2e-16] <- "< 2e-16"
c$p.adj.format[as.numeric(c$p.adj) > 0.1] <- "N.S"

c$p.adj.format.stars <- c$p.adj
c$p.adj.format.stars[c$p.adj >= 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.05] <- paste0("* (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.01] <- paste0("** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.001] <- paste0("*** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 2e-16] <- paste0("**** (p=", c$p.adj,")")

df_c <- as.data.frame(c)

plot_GSE157103.ADARB1 <-
  df_combined %>%
  filter(Project =="Leukocytes (GSE157103)") %>%
  ggplot(
               aes(y=ADARB1, x=Group))+
  geom_boxplot(aes(fill=Group)) +  geom_jitter( size=2, alpha = 0.2)+
  # facet_grid( ~ Project ,  drop = TRUE, scales = "free", space = "free",)+
  themes_ggplot+ ylab("Normalized Expression (TPM)")+ xlab ("Group")+ scale_fill_discrete(name = "Group:")+
  expand_limits(y = 0) + scale_fill_manual(values=c("blue","red"))+
  theme(axis.title.x = element_blank())+ theme(legend.position = "none")+
  geom_signif(data = df_c, 
              aes(xmin=group1, xmax=group2, annotations=p.adj.format.stars, y_position=y_pos),manual = TRUE)

## Scale for 'fill' is already present. Adding another scale for 'fill', which
## will replace the existing scale.

## Warning: Ignoring unknown aesthetics: xmin, xmax, annotations, y_position

plot_GSE157103.ADARB1

#Leukocytes (GSE157103)  Nasal Swabs (GSE166530) Whole Blood (GSE167000) Whole Blood (GSE171110)
y_position = max(df_combined%>% 
  filter(Project =="Leukocytes (GSE157103)") %>% .$ADARB2)

c <- df_combined %>% 
  filter(Project =="Leukocytes (GSE157103)") %>%
  compare_means(ADARB2 ~Group, data = .)
c %<>% mutate(y_pos = c(y_position *1), 
              labels = ifelse(p < 0.05, sprintf("%2.1e",p),p))
# c <- c[c(1,3,2),] #reorder manually sorry
c$p.adj.format <- c$p.adj
c$p.adj.format[c$p.adj < 2e-16] <- "< 2e-16"
c$p.adj.format[as.numeric(c$p.adj) > 0.1] <- "N.S"

c$p.adj.format.stars <- c$p.adj
c$p.adj.format.stars[c$p.adj >= 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.05] <- paste0("* (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.01] <- paste0("** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.001] <- paste0("*** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 2e-16] <- paste0("**** (p=", c$p.adj,")")

df_c <- as.data.frame(c)

plot_GSE157103.ADARB2 <-
  df_combined %>%
  filter(Project =="Leukocytes (GSE157103)") %>%
  ggplot(
               aes(y=ADARB2, x=Group))+
  geom_boxplot(aes(fill=Group)) +  geom_jitter( size=2, alpha = 0.2)+
  # facet_grid( ~ Project ,  drop = TRUE, scales = "free", space = "free",)+
  themes_ggplot+ ylab("Normalized Expression (TPM)")+ xlab ("Group")+ scale_fill_discrete(name = "Group:")+
  expand_limits(y = 0) + scale_fill_manual(values=c("blue","red"))+
  theme(axis.title.x = element_blank())+ theme(legend.position = "none")+
  geom_signif(data = df_c, 
              aes(xmin=group1, xmax=group2, annotations=p.adj.format.stars, y_position=y_pos),manual = TRUE)

## Scale for 'fill' is already present. Adding another scale for 'fill', which
## will replace the existing scale.

## Warning: Ignoring unknown aesthetics: xmin, xmax, annotations, y_position

plot_GSE157103.ADARB2

plot_grid(plot_GSE157103.ADAR+facet_grid(~"ADAR"), 
          plot_GSE157103.ADARB1+facet_grid(~"ADAR2"), 
          plot_GSE157103.ADARB2+facet_grid(~"ADAR3"),
          labels = c('', '',''), label_size = 12, ncol=4)

out_path <- paste0(OUT_DIR,'/',"SALMON_Leukocytes_GSE157103.pdf")
ggsave(out_path, width = 14, height = 6)

#Leukocytes (GSE157103)  Nasal Swabs (GSE166530) Whole Blood (GSE167000) Whole Blood (GSE171110)
y_position = max(df_combined%>% 
  filter(Project =="Nasal Swabs (GSE166530)") %>% .$A2GEditingIndex_Alu)

c <- df_combined %>% 
  filter(Project =="Nasal Swabs (GSE166530)") %>%
  compare_means(A2GEditingIndex_Alu ~Group, data = .)
c %<>% mutate(y_pos = c(y_position *1), 
              labels = ifelse(p < 0.05, sprintf("%2.1e",p),p))
# c <- c[c(1,3,2),] #reorder manually sorry
c$p.adj.format <- c$p.adj
c$p.adj.format[c$p.adj < 2e-16] <- "< 2e-16"
c$p.adj.format[as.numeric(c$p.adj) > 0.1] <- "N.S"

c$p.adj.format.stars <- c$p.adj
c$p.adj.format.stars[c$p.adj >= 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.05] <- paste0("* (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.01] <- paste0("** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.001] <- paste0("*** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 2e-16] <- paste0("**** (p=", c$p.adj,")")

df_c <- as.data.frame(c)

plot_GSE166530 <-
  df_combined %>%
  filter(Project =="Nasal Swabs (GSE166530)") %>%
  ggplot(
               aes(y=A2GEditingIndex_Alu, x=Group))+
  geom_boxplot(aes(fill=Group)) +  geom_jitter( size=2, alpha = 0.2)+
  facet_grid(  ~ Project ,  drop = TRUE, scales = "free", space = "free",)+
  themes_ggplot+ ylab("ALU Editing Index")+ xlab ("Group")+ scale_fill_discrete(name = "Group:")+
  expand_limits(y = 0) + scale_fill_manual(values=c("blue","red"))+
  theme(axis.title.x = element_blank())+ theme(legend.position = "none")+
  geom_signif(data = df_c, 
              aes(xmin=group1, xmax=group2, annotations=p.adj.format.stars, y_position=y_pos),manual = TRUE)

## Scale for 'fill' is already present. Adding another scale for 'fill', which
## will replace the existing scale.

## Warning: Ignoring unknown aesthetics: xmin, xmax, annotations, y_position

plot_GSE166530

#Leukocytes (GSE157103)  Nasal Swabs (GSE166530) Whole Blood (GSE167000) Whole Blood (GSE171110)
y_position = max(df_combined%>% 
  filter(Project =="Whole Blood (GSE167000)") %>% .$A2GEditingIndex_Alu)

c <- df_combined %>% 
  filter(Project =="Whole Blood (GSE167000)") %>%
  compare_means(A2GEditingIndex_Alu ~Group, data = .)
c %<>% mutate(y_pos = c(y_position *1), 
              labels = ifelse(p < 0.05, sprintf("%2.1e",p),p))
# c <- c[c(1,3,2),] #reorder manually sorry
c$p.adj.format <- c$p.adj
c$p.adj.format[c$p.adj < 2e-16] <- "< 2e-16"
c$p.adj.format[as.numeric(c$p.adj) > 0.1] <- "N.S"

c$p.adj.format.stars <- c$p.adj
c$p.adj.format.stars[c$p.adj >= 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.05] <- paste0("* (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.01] <- paste0("** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.001] <- paste0("*** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 2e-16] <- paste0("**** (p=", c$p.adj,")")

df_c <- as.data.frame(c)

plot_GSE167000 <-
  df_combined %>%
  filter(Project =="Whole Blood (GSE167000)") %>%
  ggplot(
               aes(y=A2GEditingIndex_Alu, x=Group))+
  geom_boxplot(aes(fill=Group)) +  geom_jitter( size=2, alpha = 0.2)+
  facet_grid(  ~ Project ,  drop = TRUE, scales = "free", space = "free",)+
  themes_ggplot+ ylab("ALU Editing Index")+ xlab ("Group")+ scale_fill_discrete(name = "Group:")+
  expand_limits(y = 0) + scale_fill_manual(values=c("blue","red"))+
  theme(axis.title.x = element_blank())+ theme(legend.position = "none")+
  geom_signif(data = df_c, 
              aes(xmin=group1, xmax=group2, annotations=p.adj.format.stars, y_position=y_pos),manual = TRUE)

## Scale for 'fill' is already present. Adding another scale for 'fill', which
## will replace the existing scale.

## Warning: Ignoring unknown aesthetics: xmin, xmax, annotations, y_position

plot_GSE167000

#Leukocytes (GSE157103)  Nasal Swabs (GSE166530) Whole Blood (GSE167000) Whole Blood (GSE171110)
y_position = max(df_combined%>% 
  filter(Project =="Whole Blood (GSE171110)") %>% .$A2GEditingIndex_Alu)

c <- df_combined %>% 
  filter(Project =="Whole Blood (GSE171110)") %>%
  compare_means(A2GEditingIndex_Alu ~Group, data = .)
c %<>% mutate(y_pos = c(y_position *1), 
              labels = ifelse(p < 0.05, sprintf("%2.1e",p),p))
# c <- c[c(1,3,2),] #reorder manually sorry
c$p.adj.format <- c$p.adj
c$p.adj.format[c$p.adj < 2e-16] <- "< 2e-16"
c$p.adj.format[as.numeric(c$p.adj) > 0.1] <- "N.S"

c$p.adj.format.stars <- c$p.adj
c$p.adj.format.stars[c$p.adj >= 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.05] <- paste0("* (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.01] <- paste0("** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.001] <- paste0("*** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 2e-16] <- paste0("**** (p=", c$p.adj,")")

df_c <- as.data.frame(c)

plot_GSE171110 <-
  df_combined %>%
  filter(Project =="Whole Blood (GSE171110)") %>%
  ggplot(
               aes(y=A2GEditingIndex_Alu, x=Group))+
  geom_boxplot(aes(fill=Group)) +  geom_jitter( size=2, alpha = 0.2)+
  facet_grid(  ~ Project ,  drop = TRUE, scales = "free", space = "free",)+
  themes_ggplot+ ylab("ALU Editing Index")+ xlab ("Group")+ scale_fill_discrete(name = "Group:")+
  expand_limits(y = 0) + scale_fill_manual(values=c("blue","red"))+
  theme(axis.title.x = element_blank())+ theme(legend.position = "none")+
  geom_signif(data = df_c, 
              aes(xmin=group1, xmax=group2, annotations=p.adj.format.stars, y_position=y_pos),manual = TRUE)

## Scale for 'fill' is already present. Adding another scale for 'fill', which
## will replace the existing scale.

## Warning: Ignoring unknown aesthetics: xmin, xmax, annotations, y_position

plot_GSE171110

plot_grid(plot_GSE166530, plot_GSE167000, plot_GSE171110, plot_GSE157103,
          labels = c('', '','',''), label_size = 12, ncol=4)

out_path <- paste0(OUT_DIR,'/',"AluEditing_all_combined.pdf")
ggsave(out_path, width = 14, height = 6)

Nasal Swab (GSE157103)

#Leukocytes (GSE157103)  Nasal Swabs (GSE166530) Whole Blood (GSE167000) Whole Blood (GSE171110)
y_position = max(df_combined%>% 
  filter(Project =="Nasal Swabs (GSE166530)") %>% .$ADAR)

c <- df_combined %>% 
  filter(Project =="Nasal Swabs (GSE166530)") %>%
  compare_means(ADAR ~Group, data = .)
c %<>% mutate(y_pos = c(y_position *1), 
              labels = ifelse(p < 0.05, sprintf("%2.1e",p),p))
# c <- c[c(1,3,2),] #reorder manually sorry
c$p.adj.format <- c$p.adj
c$p.adj.format[c$p.adj < 2e-16] <- "< 2e-16"
c$p.adj.format[as.numeric(c$p.adj) > 0.1] <- "N.S"

c$p.adj.format.stars <- c$p.adj
c$p.adj.format.stars[c$p.adj >= 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.05] <- paste0("* (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.01] <- paste0("** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.001] <- paste0("*** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 2e-16] <- paste0("**** (p=", c$p.adj,")")

df_c <- as.data.frame(c)

plot_GSE166530.ADAR <-
  df_combined %>%
  filter(Project =="Nasal Swabs (GSE166530)") %>%
  ggplot(
               aes(y=ADAR, x=Group))+
  geom_boxplot(aes(fill=Group)) +  geom_jitter( size=2, alpha = 0.2)+
  # facet_grid( ~ Project ,  drop = TRUE, scales = "free", space = "free",)+
  themes_ggplot+ ylab("Normalized Expression (TPM)")+ xlab ("Group")+ scale_fill_discrete(name = "Group:")+
  expand_limits(y = 0) + scale_fill_manual(values=c("blue","red"))+
  theme(axis.title.x = element_blank())+ theme(legend.position = "none")+
  geom_signif(data = df_c, 
              aes(xmin=group1, xmax=group2, annotations=p.adj.format.stars, y_position=y_pos),manual = TRUE)

## Scale for 'fill' is already present. Adding another scale for 'fill', which
## will replace the existing scale.

## Warning: Ignoring unknown aesthetics: xmin, xmax, annotations, y_position

plot_GSE166530.ADAR

#Leukocytes (GSE157103)  Nasal Swabs (GSE166530) Whole Blood (GSE167000) Whole Blood (GSE171110)
y_position = max(df_combined%>% 
  filter(Project =="Nasal Swabs (GSE166530)") %>% .$ADARB1)

c <- df_combined %>% 
  filter(Project =="Nasal Swabs (GSE166530)") %>%
  compare_means(ADARB1 ~Group, data = .)
c %<>% mutate(y_pos = c(y_position *1), 
              labels = ifelse(p < 0.05, sprintf("%2.1e",p),p))
# c <- c[c(1,3,2),] #reorder manually sorry
c$p.adj.format <- c$p.adj
c$p.adj.format[c$p.adj < 2e-16] <- "< 2e-16"
c$p.adj.format[as.numeric(c$p.adj) > 0.1] <- "N.S"

c$p.adj.format.stars <- c$p.adj
c$p.adj.format.stars[c$p.adj >= 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.05] <- paste0("* (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.01] <- paste0("** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.001] <- paste0("*** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 2e-16] <- paste0("**** (p=", c$p.adj,")")

df_c <- as.data.frame(c)

plot_GSE166530.ADARB1 <-
  df_combined %>%
  filter(Project =="Nasal Swabs (GSE166530)") %>%
  ggplot(
               aes(y=ADARB1, x=Group))+
  geom_boxplot(aes(fill=Group)) +  geom_jitter( size=2, alpha = 0.2)+
  # facet_grid( ~ Project ,  drop = TRUE, scales = "free", space = "free",)+
  themes_ggplot+ ylab("Normalized Expression (TPM)")+ xlab ("Group")+ scale_fill_discrete(name = "Group:")+
  expand_limits(y = 0) + scale_fill_manual(values=c("blue","red"))+
  theme(axis.title.x = element_blank())+ theme(legend.position = "none")+
  geom_signif(data = df_c, 
              aes(xmin=group1, xmax=group2, annotations=p.adj.format.stars, y_position=y_pos),manual = TRUE)

## Scale for 'fill' is already present. Adding another scale for 'fill', which
## will replace the existing scale.

## Warning: Ignoring unknown aesthetics: xmin, xmax, annotations, y_position

plot_GSE166530.ADARB1

#Leukocytes (GSE157103)  Nasal Swabs (GSE166530) Whole Blood (GSE167000) Whole Blood (GSE171110)
y_position = max(df_combined%>% 
  filter(Project =="Nasal Swabs (GSE166530)") %>% .$ADARB2)

c <- df_combined %>% 
  filter(Project =="Nasal Swabs (GSE166530)") %>%
  compare_means(ADARB2 ~Group, data = .)
c %<>% mutate(y_pos = c(y_position *1), 
              labels = ifelse(p < 0.05, sprintf("%2.1e",p),p))
# c <- c[c(1,3,2),] #reorder manually sorry
c$p.adj.format <- c$p.adj
c$p.adj.format[c$p.adj < 2e-16] <- "< 2e-16"
c$p.adj.format[as.numeric(c$p.adj) > 0.1] <- "N.S"

c$p.adj.format.stars <- c$p.adj
c$p.adj.format.stars[c$p.adj >= 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.05] <- paste0("* (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.01] <- paste0("** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.001] <- paste0("*** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 2e-16] <- paste0("**** (p=", c$p.adj,")")

df_c <- as.data.frame(c)

plot_GSE166530.ADARB2 <-
  df_combined %>%
  filter(Project =="Nasal Swabs (GSE166530)") %>%
  ggplot(
               aes(y=ADARB2, x=Group))+
  geom_boxplot(aes(fill=Group)) +  geom_jitter( size=2, alpha = 0.2)+
  # facet_grid( ~ Project ,  drop = TRUE, scales = "free", space = "free",)+
  themes_ggplot+ ylab("Normalized Expression (TPM)")+ xlab ("Group")+ scale_fill_discrete(name = "Group:")+
  expand_limits(y = 0) + scale_fill_manual(values=c("blue","red"))+
  theme(axis.title.x = element_blank())+ theme(legend.position = "none")+
  geom_signif(data = df_c, 
              aes(xmin=group1, xmax=group2, annotations=p.adj.format.stars, y_position=y_pos),manual = TRUE)

## Scale for 'fill' is already present. Adding another scale for 'fill', which
## will replace the existing scale.

## Warning: Ignoring unknown aesthetics: xmin, xmax, annotations, y_position

plot_GSE166530.ADARB2

plot_grid(plot_GSE166530.ADAR+facet_grid(~"ADAR"), 
          plot_GSE166530.ADARB1+facet_grid(~"ADAR2"), 
          plot_GSE166530.ADARB2+facet_grid(~"ADAR3"),
          labels = c('', '',''), label_size = 12, ncol=4)

out_path <- paste0(OUT_DIR,'/',"SALMON_Nasal Swabs_GSE166530.pdf")
ggsave(out_path, width = 14, height = 6)

Whole Blood (GSE167000)

#Leukocytes (GSE157103)  Nasal Swabs (GSE166530) Whole Blood (GSE167000) Whole Blood (GSE171110)
y_position = max(df_combined%>% 
  filter(Project =="Whole Blood (GSE167000)") %>% .$ADAR, na.rm=T)

c <- df_combined %>% 
  filter(Project =="Whole Blood (GSE167000)") %>%
  compare_means(ADAR ~Group, data = .)
c %<>% mutate(y_pos = c(y_position *1), 
              labels = ifelse(p < 0.05, sprintf("%2.1e",p),p))
# c <- c[c(1,3,2),] #reorder manually sorry
c$p.adj.format <- c$p.adj
c$p.adj.format[c$p.adj < 2e-16] <- "< 2e-16"
c$p.adj.format[as.numeric(c$p.adj) > 0.1] <- "N.S"

c$p.adj.format.stars <- c$p.adj
c$p.adj.format.stars[c$p.adj >= 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.05] <- paste0("* (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.01] <- paste0("** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.001] <- paste0("*** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 2e-16] <- paste0("**** (p=", c$p.adj,")")

df_c <- as.data.frame(c)

plot_GSE167000.ADAR <-
  df_combined %>% 
  filter(Project =="Whole Blood (GSE167000)") %>%
  ggplot(
               aes(y=ADAR, x=Group))+
  geom_boxplot(aes(fill=Group)) +  geom_jitter( size=2, alpha = 0.2)+
  # facet_grid( ~ Project ,  drop = TRUE, scales = "free", space = "free",)+
  themes_ggplot+ ylab("Normalized Expression (TPM)")+ xlab ("Group")+ scale_fill_discrete(name = "Group:")+
  expand_limits(y = 0) + scale_fill_manual(values=c("blue","red"))+
  theme(axis.title.x = element_blank())+ theme(legend.position = "none")+
  geom_signif(data = df_c, 
              aes(xmin=group1, xmax=group2, annotations=p.adj.format.stars, y_position=y_pos),manual = TRUE)

## Scale for 'fill' is already present. Adding another scale for 'fill', which
## will replace the existing scale.

## Warning: Ignoring unknown aesthetics: xmin, xmax, annotations, y_position

plot_GSE167000.ADAR

## Warning: Removed 51 rows containing non-finite values (stat_boxplot).

## Warning: Removed 51 rows containing missing values (geom_point).

#Leukocytes (GSE157103)  Nasal Swabs (GSE166530) Whole Blood (GSE167000) Whole Blood (GSE171110)
y_position = max(df_combined%>% 
  filter(Project =="Whole Blood (GSE167000)") %>% .$ADARB1, na.rm=T)

c <- df_combined %>% 
  filter(Project =="Whole Blood (GSE167000)") %>%
  compare_means(ADARB1 ~Group, data = .)
c %<>% mutate(y_pos = c(y_position *1), 
              labels = ifelse(p < 0.05, sprintf("%2.1e",p),p))
# c <- c[c(1,3,2),] #reorder manually sorry
c$p.adj.format <- c$p.adj
c$p.adj.format[c$p.adj < 2e-16] <- "< 2e-16"
c$p.adj.format[as.numeric(c$p.adj) > 0.1] <- "N.S"

c$p.adj.format.stars <- c$p.adj
c$p.adj.format.stars[c$p.adj >= 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.05] <- paste0("* (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.01] <- paste0("** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.001] <- paste0("*** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 2e-16] <- paste0("**** (p=", c$p.adj,")")

df_c <- as.data.frame(c)

plot_GSE167000.ADARB1 <-
  df_combined %>%
  filter(Project =="Whole Blood (GSE167000)") %>%
  ggplot(
               aes(y=ADARB1, x=Group))+
  geom_boxplot(aes(fill=Group)) +  geom_jitter( size=2, alpha = 0.2)+
  # facet_grid( ~ Project ,  drop = TRUE, scales = "free", space = "free",)+
  themes_ggplot+ ylab("Normalized Expression (TPM)")+ xlab ("Group")+ scale_fill_discrete(name = "Group:")+
  expand_limits(y = 0) + scale_fill_manual(values=c("blue","red"))+
  theme(axis.title.x = element_blank())+ theme(legend.position = "none")+
  geom_signif(data = df_c, 
              aes(xmin=group1, xmax=group2, annotations=p.adj.format.stars, y_position=y_pos),manual = TRUE)

## Scale for 'fill' is already present. Adding another scale for 'fill', which
## will replace the existing scale.

## Warning: Ignoring unknown aesthetics: xmin, xmax, annotations, y_position

plot_GSE167000.ADARB1

## Warning: Removed 51 rows containing non-finite values (stat_boxplot).

## Warning: Removed 51 rows containing missing values (geom_point).

#Leukocytes (GSE157103)  Nasal Swabs (GSE166530) Whole Blood (GSE167000) Whole Blood (GSE171110)
y_position = max(df_combined%>% 
  filter(Project =="Whole Blood (GSE167000)") %>% .$ADARB2,na.rm=T)

c <- df_combined %>% 
  filter(Project =="Whole Blood (GSE167000)") %>%
  compare_means(ADARB2 ~Group, data = .)
c %<>% mutate(y_pos = c(y_position *1), 
              labels = ifelse(p < 0.05, sprintf("%2.1e",p),p))
# c <- c[c(1,3,2),] #reorder manually sorry
c$p.adj.format <- c$p.adj
c$p.adj.format[c$p.adj < 2e-16] <- "< 2e-16"
c$p.adj.format[as.numeric(c$p.adj) > 0.1] <- "N.S"

c$p.adj.format.stars <- c$p.adj
c$p.adj.format.stars[c$p.adj >= 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.05] <- paste0("* (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.01] <- paste0("** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.001] <- paste0("*** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 2e-16] <- paste0("**** (p=", c$p.adj,")")

df_c <- as.data.frame(c)

plot_GSE167000.ADARB2 <-
  df_combined %>%
  filter(Project =="Whole Blood (GSE167000)") %>%
  ggplot(
               aes(y=ADARB2, x=Group))+
  geom_boxplot(aes(fill=Group)) +  geom_jitter( size=2, alpha = 0.2)+
  # facet_grid( ~ Project ,  drop = TRUE, scales = "free", space = "free",)+
  themes_ggplot+ ylab("Normalized Expression (TPM)")+ xlab ("Group")+ scale_fill_discrete(name = "Group:")+
  expand_limits(y = 0) + scale_fill_manual(values=c("blue","red"))+
  theme(axis.title.x = element_blank())+ theme(legend.position = "none")+
  geom_signif(data = df_c, 
              aes(xmin=group1, xmax=group2, annotations=p.adj.format.stars, y_position=y_pos),manual = TRUE)

## Scale for 'fill' is already present. Adding another scale for 'fill', which
## will replace the existing scale.

## Warning: Ignoring unknown aesthetics: xmin, xmax, annotations, y_position

plot_GSE167000.ADARB2

## Warning: Removed 51 rows containing non-finite values (stat_boxplot).

## Warning: Removed 51 rows containing missing values (geom_point).

plot_grid(plot_GSE167000.ADAR+facet_grid(~"ADAR"), 
          plot_GSE167000.ADARB1+facet_grid(~"ADAR2"), 
          plot_GSE167000.ADARB2+facet_grid(~"ADAR3"),
          labels = c('', '',''), label_size = 12, ncol=4)

## Warning: Removed 51 rows containing non-finite values (stat_boxplot).

## Warning: Removed 51 rows containing missing values (geom_point).

## Warning: Removed 51 rows containing non-finite values (stat_boxplot).

## Warning: Removed 51 rows containing missing values (geom_point).

## Warning: Removed 51 rows containing non-finite values (stat_boxplot).

## Warning: Removed 51 rows containing missing values (geom_point).

out_path <- paste0(OUT_DIR,'/',"SALMON_WholeBlood_GSE167000.pdf")
ggsave(out_path, width = 14, height = 6)

#Leukocytes (GSE157103)  Nasal Swabs (GSE166530) Whole Blood (GSE167000) Whole Blood (GSE171110)
y_position = max(df_combined%>% 
  filter(Project =="Nasal Swabs (GSE166530)") %>% .$A2GEditingIndex_Alu)

c <- df_combined %>% 
  filter(Project =="Nasal Swabs (GSE166530)") %>%
  compare_means(A2GEditingIndex_Alu ~Group, data = .)
c %<>% mutate(y_pos = c(y_position *1), 
              labels = ifelse(p < 0.05, sprintf("%2.1e",p),p))
# c <- c[c(1,3,2),] #reorder manually sorry
c$p.adj.format <- c$p.adj
c$p.adj.format[c$p.adj < 2e-16] <- "< 2e-16"
c$p.adj.format[as.numeric(c$p.adj) > 0.1] <- "N.S"

c$p.adj.format.stars <- c$p.adj
c$p.adj.format.stars[c$p.adj >= 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.05] <- paste0("* (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.01] <- paste0("** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.001] <- paste0("*** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 2e-16] <- paste0("**** (p=", c$p.adj,")")

df_c <- as.data.frame(c)

plot_GSE166530 <-
  df_combined %>%
  filter(Project =="Nasal Swabs (GSE166530)") %>%
  ggplot(
               aes(y=A2GEditingIndex_Alu, x=Group))+
  geom_boxplot(aes(fill=Group)) +  geom_jitter( size=2, alpha = 0.2)+
  facet_grid(  ~ Project ,  drop = TRUE, scales = "free", space = "free",)+
  themes_ggplot+ ylab("ALU Editing Index")+ xlab ("Group")+ scale_fill_discrete(name = "Group:")+
  expand_limits(y = 0) + scale_fill_manual(values=c("blue","red"))+
  theme(axis.title.x = element_blank())+ theme(legend.position = "none")+
  geom_signif(data = df_c, 
              aes(xmin=group1, xmax=group2, annotations=p.adj.format.stars, y_position=y_pos),manual = TRUE)

## Scale for 'fill' is already present. Adding another scale for 'fill', which
## will replace the existing scale.

## Warning: Ignoring unknown aesthetics: xmin, xmax, annotations, y_position

plot_GSE166530

#Leukocytes (GSE157103)  Nasal Swabs (GSE166530) Whole Blood (GSE167000) Whole Blood (GSE171110)
y_position = max(df_combined%>% 
  filter(Project =="Whole Blood (GSE167000)") %>% .$A2GEditingIndex_Alu)

c <- df_combined %>% 
  filter(Project =="Whole Blood (GSE167000)") %>%
  compare_means(A2GEditingIndex_Alu ~Group, data = .)
c %<>% mutate(y_pos = c(y_position *1), 
              labels = ifelse(p < 0.05, sprintf("%2.1e",p),p))
# c <- c[c(1,3,2),] #reorder manually sorry
c$p.adj.format <- c$p.adj
c$p.adj.format[c$p.adj < 2e-16] <- "< 2e-16"
c$p.adj.format[as.numeric(c$p.adj) > 0.1] <- "N.S"

c$p.adj.format.stars <- c$p.adj
c$p.adj.format.stars[c$p.adj >= 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.05] <- paste0("* (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.01] <- paste0("** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.001] <- paste0("*** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 2e-16] <- paste0("**** (p=", c$p.adj,")")

df_c <- as.data.frame(c)

plot_GSE167000 <-
  df_combined %>%
  filter(Project =="Whole Blood (GSE167000)") %>%
  ggplot(
               aes(y=A2GEditingIndex_Alu, x=Group))+
  geom_boxplot(aes(fill=Group)) +  geom_jitter( size=2, alpha = 0.2)+
  facet_grid(  ~ Project ,  drop = TRUE, scales = "free", space = "free",)+
  themes_ggplot+ ylab("ALU Editing Index")+ xlab ("Group")+ scale_fill_discrete(name = "Group:")+
  expand_limits(y = 0) + scale_fill_manual(values=c("blue","red"))+
  theme(axis.title.x = element_blank())+ theme(legend.position = "none")+
  geom_signif(data = df_c, 
              aes(xmin=group1, xmax=group2, annotations=p.adj.format.stars, y_position=y_pos),manual = TRUE)

## Scale for 'fill' is already present. Adding another scale for 'fill', which
## will replace the existing scale.

## Warning: Ignoring unknown aesthetics: xmin, xmax, annotations, y_position

plot_GSE167000

#Leukocytes (GSE157103)  Nasal Swabs (GSE166530) Whole Blood (GSE167000) Whole Blood (GSE171110)
y_position = max(df_combined%>% 
  filter(Project =="Whole Blood (GSE171110)") %>% .$A2GEditingIndex_Alu)

c <- df_combined %>% 
  filter(Project =="Whole Blood (GSE171110)") %>%
  compare_means(A2GEditingIndex_Alu ~Group, data = .)
c %<>% mutate(y_pos = c(y_position *1), 
              labels = ifelse(p < 0.05, sprintf("%2.1e",p),p))
# c <- c[c(1,3,2),] #reorder manually sorry
c$p.adj.format <- c$p.adj
c$p.adj.format[c$p.adj < 2e-16] <- "< 2e-16"
c$p.adj.format[as.numeric(c$p.adj) > 0.1] <- "N.S"

c$p.adj.format.stars <- c$p.adj
c$p.adj.format.stars[c$p.adj >= 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.05] <- paste0("* (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.01] <- paste0("** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.001] <- paste0("*** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 2e-16] <- paste0("**** (p=", c$p.adj,")")

df_c <- as.data.frame(c)

plot_GSE171110 <-
  df_combined %>%
  filter(Project =="Whole Blood (GSE171110)") %>%
  ggplot(
               aes(y=A2GEditingIndex_Alu, x=Group))+
  geom_boxplot(aes(fill=Group)) +  geom_jitter( size=2, alpha = 0.2)+
  facet_grid(  ~ Project ,  drop = TRUE, scales = "free", space = "free",)+
  themes_ggplot+ ylab("ALU Editing Index")+ xlab ("Group")+ scale_fill_discrete(name = "Group:")+
  expand_limits(y = 0) + scale_fill_manual(values=c("blue","red"))+
  theme(axis.title.x = element_blank())+ theme(legend.position = "none")+
  geom_signif(data = df_c, 
              aes(xmin=group1, xmax=group2, annotations=p.adj.format.stars, y_position=y_pos),manual = TRUE)

## Scale for 'fill' is already present. Adding another scale for 'fill', which
## will replace the existing scale.

## Warning: Ignoring unknown aesthetics: xmin, xmax, annotations, y_position

plot_GSE171110

plot_grid(plot_GSE166530, plot_GSE167000, plot_GSE171110, plot_GSE157103,
          labels = c('', '','',''), label_size = 12, ncol=4)

out_path <- paste0(OUT_DIR,'/',"AluEditing_all_combined.pdf")
ggsave(out_path, width = 14, height = 6)

Nasal Swabs (GSE166530)

Whole Blood (GSE167000)

#Leukocytes (GSE157103)  Nasal Swabs (GSE166530) Whole Blood (GSE167000) Whole Blood (GSE171110)
y_position = max(df_combined%>% 
  filter(Project =="Whole Blood (GSE171110)") %>% .$ADAR, na.rm=T)

c <- df_combined %>% 
  filter(Project =="Whole Blood (GSE171110)") %>%
  compare_means(ADAR ~Group, data = .)
c %<>% mutate(y_pos = c(y_position *1), 
              labels = ifelse(p < 0.05, sprintf("%2.1e",p),p))
# c <- c[c(1,3,2),] #reorder manually sorry
c$p.adj.format <- c$p.adj
c$p.adj.format[c$p.adj < 2e-16] <- "< 2e-16"
c$p.adj.format[as.numeric(c$p.adj) > 0.1] <- "N.S"

c$p.adj.format.stars <- c$p.adj
c$p.adj.format.stars[c$p.adj >= 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.05] <- paste0("* (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.01] <- paste0("** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.001] <- paste0("*** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 2e-16] <- paste0("**** (p=", c$p.adj,")")

df_c <- as.data.frame(c)

plot_GSE171110.ADAR <-
  df_combined %>% 
  filter(Project =="Whole Blood (GSE171110)") %>%
  ggplot(
               aes(y=ADAR, x=Group))+
  geom_boxplot(aes(fill=Group)) +  geom_jitter( size=2, alpha = 0.2)+
  # facet_grid( ~ Project ,  drop = TRUE, scales = "free", space = "free",)+
  themes_ggplot+ ylab("Normalized Expression (TPM)")+ xlab ("Group")+ scale_fill_discrete(name = "Group:")+
  expand_limits(y = 0) + scale_fill_manual(values=c("blue","red"))+
  theme(axis.title.x = element_blank())+ theme(legend.position = "none")+
  geom_signif(data = df_c, 
              aes(xmin=group1, xmax=group2, annotations=p.adj.format.stars, y_position=y_pos),manual = TRUE)

## Scale for 'fill' is already present. Adding another scale for 'fill', which
## will replace the existing scale.

## Warning: Ignoring unknown aesthetics: xmin, xmax, annotations, y_position

plot_GSE171110.ADAR

#Leukocytes (GSE157103)  Nasal Swabs (GSE166530) Whole Blood (GSE167000) Whole Blood (GSE171110)
y_position = max(df_combined%>% 
  filter(Project =="Whole Blood (GSE171110)") %>% .$ADARB1, na.rm=T)

c <- df_combined %>% 
  filter(Project =="Whole Blood (GSE171110)") %>%
  compare_means(ADARB1 ~Group, data = .)
c %<>% mutate(y_pos = c(y_position *1), 
              labels = ifelse(p < 0.05, sprintf("%2.1e",p),p))
# c <- c[c(1,3,2),] #reorder manually sorry
c$p.adj.format <- c$p.adj
c$p.adj.format[c$p.adj < 2e-16] <- "< 2e-16"
c$p.adj.format[as.numeric(c$p.adj) > 0.1] <- "N.S"

c$p.adj.format.stars <- c$p.adj
c$p.adj.format.stars[c$p.adj >= 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.05] <- paste0("* (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.01] <- paste0("** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.001] <- paste0("*** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 2e-16] <- paste0("**** (p=", c$p.adj,")")

df_c <- as.data.frame(c)

plot_GSE171110.ADARB1 <-
  df_combined %>%
  filter(Project =="Whole Blood (GSE171110)") %>%
  ggplot(
               aes(y=ADARB1, x=Group))+
  geom_boxplot(aes(fill=Group)) +  geom_jitter( size=2, alpha = 0.2)+
  # facet_grid( ~ Project ,  drop = TRUE, scales = "free", space = "free",)+
  themes_ggplot+ ylab("Normalized Expression (TPM)")+ xlab ("Group")+ scale_fill_discrete(name = "Group:")+
  expand_limits(y = 0) + scale_fill_manual(values=c("blue","red"))+
  theme(axis.title.x = element_blank())+ theme(legend.position = "none")+
  geom_signif(data = df_c, 
              aes(xmin=group1, xmax=group2, annotations=p.adj.format.stars, y_position=y_pos),manual = TRUE)

## Scale for 'fill' is already present. Adding another scale for 'fill', which
## will replace the existing scale.

## Warning: Ignoring unknown aesthetics: xmin, xmax, annotations, y_position

plot_GSE171110.ADARB1

#Leukocytes (GSE157103)  Nasal Swabs (GSE166530) Whole Blood (GSE167000) Whole Blood (GSE171110)
y_position = max(df_combined%>% 
  filter(Project =="Whole Blood (GSE171110)") %>% .$ADARB2,na.rm=T)

c <- df_combined %>% 
  filter(Project =="Whole Blood (GSE171110)") %>%
  compare_means(ADARB2 ~Group, data = .)
c %<>% mutate(y_pos = c(y_position *1), 
              labels = ifelse(p < 0.05, sprintf("%2.1e",p),p))
# c <- c[c(1,3,2),] #reorder manually sorry
c$p.adj.format <- c$p.adj
c$p.adj.format[c$p.adj < 2e-16] <- "< 2e-16"
c$p.adj.format[as.numeric(c$p.adj) > 0.1] <- "N.S"

c$p.adj.format.stars <- c$p.adj
c$p.adj.format.stars[c$p.adj >= 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.05] <- paste0("* (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.01] <- paste0("** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.001] <- paste0("*** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 2e-16] <- paste0("**** (p=", c$p.adj,")")

df_c <- as.data.frame(c)

plot_GSE171110.ADARB2 <-
  df_combined %>%
  filter(Project =="Whole Blood (GSE171110)") %>%
  ggplot(
               aes(y=ADARB2, x=Group))+
  geom_boxplot(aes(fill=Group)) +  geom_jitter( size=2, alpha = 0.2)+
  # facet_grid( ~ Project ,  drop = TRUE, scales = "free", space = "free",)+
  themes_ggplot+ ylab("Normalized Expression (TPM)")+ xlab ("Group")+ scale_fill_discrete(name = "Group:")+
  expand_limits(y = 0) + scale_fill_manual(values=c("blue","red"))+
  theme(axis.title.x = element_blank())+ theme(legend.position = "none")+
  geom_signif(data = df_c, 
              aes(xmin=group1, xmax=group2, annotations=p.adj.format.stars, y_position=y_pos),manual = TRUE)

## Scale for 'fill' is already present. Adding another scale for 'fill', which
## will replace the existing scale.

## Warning: Ignoring unknown aesthetics: xmin, xmax, annotations, y_position

plot_GSE171110.ADARB2

#Leukocytes (GSE157103)  Nasal Swabs (GSE166530) Whole Blood (GSE167000) Whole Blood (GSE171110)

plot_grid(plot_GSE171110.ADAR+facet_grid(~"ADAR"), 
          plot_GSE171110.ADARB1+facet_grid(~"ADAR2"), 
          plot_GSE171110.ADARB2+facet_grid(~"ADAR3"),
          labels = c('', '',''), label_size = 12, ncol=4)

out_path <- paste0(OUT_DIR,'/',"SALMON_WholeBlood_GSE171110.pdf")
ggsave(out_path, width = 14, height = 6)

All datasets

#Leukocytes (GSE157103)  Nasal Swabs (GSE166530) Whole Blood (GSE167000) Whole Blood (GSE171110)

 plot_grid(plot_GSE166530.ADAR+facet_grid(~"Nasal Swabs (GSE166530)"), 
          plot_GSE167000.ADAR+facet_grid(~"Whole Blood (GSE167000)"),
          plot_GSE171110.ADAR+facet_grid(~"Whole Blood (GSE171110)"),
          plot_GSE157103.ADAR+facet_grid(~"Leukocytes (GSE157103)"),
          labels = c('', '','',''), label_size = 12, ncol=4)

## Warning: Removed 51 rows containing non-finite values (stat_boxplot).

## Warning: Removed 51 rows containing missing values (geom_point).

out_path <- paste0(OUT_DIR,'/',"SALMON_All_adar1.pdf")
ggsave(out_path, width = 16, height = 6)         

ISG

#Leukocytes (GSE157103)  Nasal Swabs (GSE166530) Whole Blood (GSE167000) Whole Blood (GSE171110)
y_position = max(df_combined%>% 
  filter(Project =="Leukocytes (GSE157103)") %>% .$ISG38_score)

c <- df_combined %>% 
  filter(Project =="Leukocytes (GSE157103)") %>%
  compare_means(ISG38_score ~Group, data = .)
c %<>% mutate(y_pos = c(y_position *1), 
              labels = ifelse(p < 0.05, sprintf("%2.1e",p),p))
# c <- c[c(1,3,2),] #reorder manually sorry
c$p.adj.format <- c$p.adj
c$p.adj.format[c$p.adj < 2e-16] <- "< 2e-16"
c$p.adj.format[as.numeric(c$p.adj) > 0.1] <- "N.S"

c$p.adj.format.stars <- c$p.adj
c$p.adj.format.stars[c$p.adj >= 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.05] <- paste0("* (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.01] <- paste0("** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.001] <- paste0("*** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 2e-16] <- paste0("**** (p=", c$p.adj,")")

df_c <- as.data.frame(c)

plot_GSE157103 <-
  df_combined %>%
  filter(Project =="Leukocytes (GSE157103)") %>%
  ggplot(
               aes(y=ISG38_score, x=Group))+
  geom_boxplot(aes(fill=Group)) +  geom_jitter( size=2, alpha = 0.2)+
  facet_grid(  ~ Project ,  drop = TRUE, scales = "free", space = "free",)+
  themes_ggplot+ ylab("Interferon signalling genes")+ xlab ("Group")+ scale_fill_discrete(name = "Group:")+
  expand_limits(y = 0) + scale_fill_manual(values=c("blue","red"))+
  theme(axis.title.x = element_blank())+ theme(legend.position = "none")+
  geom_signif(data = df_c, 
              aes(xmin=group1, xmax=group2, annotations=p.adj.format.stars, y_position=y_pos),manual = TRUE)

## Scale for 'fill' is already present. Adding another scale for 'fill', which
## will replace the existing scale.

## Warning: Ignoring unknown aesthetics: xmin, xmax, annotations, y_position

plot_GSE157103

#Leukocytes (GSE157103)  Nasal Swabs (GSE166530) Whole Blood (GSE167000) Whole Blood (GSE171110)
y_position = max(df_combined%>% 
  filter(Project =="Nasal Swabs (GSE166530)") %>% .$ISG38_score)

c <- df_combined %>% 
  filter(Project =="Nasal Swabs (GSE166530)") %>%
  compare_means(ISG38_score ~Group, data = .)
c %<>% mutate(y_pos = c(y_position *1), 
              labels = ifelse(p < 0.05, sprintf("%2.1e",p),p))
# c <- c[c(1,3,2),] #reorder manually sorry
c$p.adj.format <- c$p.adj
c$p.adj.format[c$p.adj < 2e-16] <- "< 2e-16"
c$p.adj.format[as.numeric(c$p.adj) > 0.1] <- "N.S"

c$p.adj.format.stars <- c$p.adj
c$p.adj.format.stars[c$p.adj >= 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.05] <- paste0("* (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.01] <- paste0("** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.001] <- paste0("*** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 2e-16] <- paste0("**** (p=", c$p.adj,")")

df_c <- as.data.frame(c)

plot_GSE166530 <-
  df_combined %>%
  filter(Project =="Nasal Swabs (GSE166530)") %>%
  ggplot(
               aes(y=ISG38_score, x=Group))+
  geom_boxplot(aes(fill=Group)) +  geom_jitter( size=2, alpha = 0.2)+
  facet_grid(  ~ Project ,  drop = TRUE, scales = "free", space = "free",)+
  themes_ggplot+ ylab("Interferon signalling genes")+ xlab ("Group")+ scale_fill_discrete(name = "Group:")+
  expand_limits(y = 0) + scale_fill_manual(values=c("blue","red"))+
  theme(axis.title.x = element_blank())+ theme(legend.position = "none")+
  geom_signif(data = df_c, 
              aes(xmin=group1, xmax=group2, annotations=p.adj.format.stars, y_position=y_pos),manual = TRUE)

## Scale for 'fill' is already present. Adding another scale for 'fill', which
## will replace the existing scale.

## Warning: Ignoring unknown aesthetics: xmin, xmax, annotations, y_position

plot_GSE166530

#Leukocytes (GSE157103)  Nasal Swabs (GSE166530) Whole Blood (GSE167000) Whole Blood (GSE171110)
y_position = max(df_combined%>% 
  filter(Project =="Whole Blood (GSE167000)") %>% .$ISG38_score)

c <- df_combined %>% 
  filter(Project =="Whole Blood (GSE167000)") %>%
  compare_means(ISG38_score ~Group, data = .)
c %<>% mutate(y_pos = c(y_position *1), 
              labels = ifelse(p < 0.05, sprintf("%2.1e",p),p))
# c <- c[c(1,3,2),] #reorder manually sorry
c$p.adj.format <- c$p.adj
c$p.adj.format[c$p.adj < 2e-16] <- "< 2e-16"
c$p.adj.format[as.numeric(c$p.adj) > 0.1] <- "N.S"

c$p.adj.format.stars <- c$p.adj
c$p.adj.format.stars[c$p.adj >= 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.05] <- paste0("* (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.01] <- paste0("** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.001] <- paste0("*** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 2e-16] <- paste0("**** (p=", c$p.adj,")")

df_c <- as.data.frame(c)

plot_GSE167000 <-
  df_combined %>%
  filter(Project =="Whole Blood (GSE167000)") %>%
  ggplot(
               aes(y=ISG38_score, x=Group))+
  geom_boxplot(aes(fill=Group)) +  geom_jitter( size=2, alpha = 0.2)+
  facet_grid(  ~ Project ,  drop = TRUE, scales = "free", space = "free",)+
  themes_ggplot+ ylab("Interferon signalling genes")+ xlab ("Group")+ scale_fill_discrete(name = "Group:")+
  expand_limits(y = 0) + scale_fill_manual(values=c("blue","red"))+
  theme(axis.title.x = element_blank())+ theme(legend.position = "none")+
  geom_signif(data = df_c, 
              aes(xmin=group1, xmax=group2, annotations=p.adj.format.stars, y_position=y_pos),manual = TRUE)

## Scale for 'fill' is already present. Adding another scale for 'fill', which
## will replace the existing scale.

## Warning: Ignoring unknown aesthetics: xmin, xmax, annotations, y_position

plot_GSE167000

#Leukocytes (GSE157103)  Nasal Swabs (GSE166530) Whole Blood (GSE167000) Whole Blood (GSE171110)
y_position = max(df_combined%>% 
  filter(Project =="Whole Blood (GSE171110)") %>% .$ISG38_score)

c <- df_combined %>% 
  filter(Project =="Whole Blood (GSE171110)") %>%
  compare_means(ISG38_score ~Group, data = .)
c %<>% mutate(y_pos = c(y_position *1), 
              labels = ifelse(p < 0.05, sprintf("%2.1e",p),p))
# c <- c[c(1,3,2),] #reorder manually sorry
c$p.adj.format <- c$p.adj
c$p.adj.format[c$p.adj < 2e-16] <- "< 2e-16"
c$p.adj.format[as.numeric(c$p.adj) > 0.1] <- "N.S"

c$p.adj.format.stars <- c$p.adj
c$p.adj.format.stars[c$p.adj >= 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.1] <- "ns"
c$p.adj.format.stars[c$p.adj < 0.05] <- paste0("* (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.01] <- paste0("** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 0.001] <- paste0("*** (p=", c$p.adj,")")
c$p.adj.format.stars[c$p.adj < 2e-16] <- paste0("**** (p=", c$p.adj,")")

df_c <- as.data.frame(c)

plot_GSE171110 <-
  df_combined %>%
  filter(Project =="Whole Blood (GSE171110)") %>%
  ggplot(
               aes(y=ISG38_score, x=Group))+
  geom_boxplot(aes(fill=Group)) +  geom_jitter( size=2, alpha = 0.2)+
  facet_grid(  ~ Project ,  drop = TRUE, scales = "free", space = "free",)+
  themes_ggplot+ ylab("Interferon signalling genes")+ xlab ("Group")+ scale_fill_discrete(name = "Group:")+
  expand_limits(y = 0) + scale_fill_manual(values=c("blue","red"))+
  theme(axis.title.x = element_blank())+ theme(legend.position = "none")+
  geom_signif(data = df_c, 
              aes(xmin=group1, xmax=group2, annotations=p.adj.format.stars, y_position=y_pos),manual = TRUE)

## Scale for 'fill' is already present. Adding another scale for 'fill', which
## will replace the existing scale.

## Warning: Ignoring unknown aesthetics: xmin, xmax, annotations, y_position

plot_GSE171110

plot_grid(plot_GSE166530, plot_GSE167000, plot_GSE171110, plot_GSE157103,
          labels = c('', '','',''), label_size = 12, ncol=4)

out_path <- paste0(OUT_DIR,'/',"ISG_all_combined.pdf")
ggsave(out_path, width = 14, height = 6)

correlation

corr_alu_ADAR <- df_combined %>% 
  ggplot(aes(y=A2GEditingIndex_Alu, x=ADAR))+ facet_wrap(~Project)+
  geom_point(aes(color=Group),size=3, alpha = 0.4) + themes_ggplot+ geom_smooth(method='lm', se=F, colour ="black")+
  stat_cor(method = "pearson", label.x.npc = "left", label.y.npc = "top") + scale_color_manual(values=c("blue","red"), name = "Group:") +
  ylab("ALU Editing Index")+ xlab ("ADAR1 Normalized Expression (TPM)")

corr_alu_ADAR

## `geom_smooth()` using formula 'y ~ x'

## Warning: Removed 51 rows containing non-finite values (stat_smooth).

## Warning: Removed 51 rows containing non-finite values (stat_cor).

## Warning: Removed 51 rows containing missing values (geom_point).

out_path <- paste0(OUT_DIR,'/',"corr_Alu_ADAR.pdf")
ggsave(out_path, corr_alu_ADAR, width = 10, height = 6)

## `geom_smooth()` using formula 'y ~ x'

## Warning: Removed 51 rows containing non-finite values (stat_smooth).

## Warning: Removed 51 rows containing non-finite values (stat_cor).

## Warning: Removed 51 rows containing missing values (geom_point).

corr_ISG_ADAR <- df_combined %>% 
ggplot(aes(y=ISG38_score, x=ADAR))+
  geom_point(aes(color=Group),size=3, alpha = 0.4) + themes_ggplot+ geom_smooth(method='lm', se=F, colour ="black")+
  facet_wrap(~Project)+
  stat_cor(method = "pearson", label.x.npc = "left", label.y.npc = "top") + scale_color_manual(values=c("blue","red"), name = "Group:") +
  ylab("Interferon-Stimulated Genes Score")+ xlab ("ADAR1 Normalized Expression (TPM)")

corr_ISG_ADAR

## `geom_smooth()` using formula 'y ~ x'

## Warning: Removed 51 rows containing non-finite values (stat_smooth).

## Warning: Removed 51 rows containing non-finite values (stat_cor).

## Warning: Removed 51 rows containing missing values (geom_point).

out_path <- paste0(OUT_DIR,'/',"corr_ISG_ADAR.pdf")
ggsave(out_path, corr_ISG_ADAR, width = 10, height = 6)

## `geom_smooth()` using formula 'y ~ x'

## Warning: Removed 51 rows containing non-finite values (stat_smooth).

## Warning: Removed 51 rows containing non-finite values (stat_cor).

## Warning: Removed 51 rows containing missing values (geom_point).

corr_ISG_Alu <- df_combined %>% 
ggplot(aes(x=A2GEditingIndex_Alu, y=ISG38_score))+
  geom_point(aes(color=Group),size=3, alpha = 0.4) + 
  themes_ggplot+ geom_smooth(method='lm', se=F, colour ="black")+ facet_wrap(~Project)+
  stat_cor(method = "pearson", label.x.npc = "left", label.y.npc = "top") + scale_color_manual(values=c("blue","red"), name = "Group:") +
  xlab("Interferon-Stimulated Genes Score")+ ylab (" ALU Editing Index")

corr_ISG_Alu

## `geom_smooth()` using formula 'y ~ x'

out_path <- paste0(OUT_DIR,'/',"corr_corr_ISG_Alu.pdf")
ggsave(out_path, corr_ISG_ADAR, width = 10, height = 6)

## `geom_smooth()` using formula 'y ~ x'

## Warning: Removed 51 rows containing non-finite values (stat_smooth).

## Warning: Removed 51 rows containing non-finite values (stat_cor).

## Warning: Removed 51 rows containing missing values (geom_point).